Perception is an inferential process, in which sensory inputs and prior knowledge are combined to arrive at a best guess of what is in the world. In line with this, previous studies have shown that expectations strongly modulate neural signals in sensory cortices. However, most of these studies have focused on expectations about simple features, such as the orientation or spatial location of a grating. This stands in contrast to daily life, where expectations often pertain to more complex objects, such as the expectation of seeing a dog upon hearing a bark. In the current study, we used auditory cues to manipulate the predictability of complex shapes that were defined along a continuum of Fourier descriptors. With high-resolution fMRI, we found that the univariate neural response to invalidly predicted shapes was delayed with respect to validly predicted shapes throughout visual cortex (e.g., in V1, V2, and lateral occipital cortex). Not only was the overall response delayed, but so too was the information present in neural activity patterns. Specifically, we trained an inverted encoding model on shapes in the absence of predictions, and used this model to reconstruct what these visual areas represented when a shape was validly and invalidly predicted. The same shape was presented in both cases, but there was a marked delay in information about this shape when it was invalidly predicted. These results suggest that invalid expectations interfere with shape processing throughout the visual cortical hierarchy. Moreover, the fact that predictions about complex shape change the timing of neural responses stands in contrast to the effect of predictions about simple features, which modulate the amplitude of response. This discrepancy suggests that different neural mechanisms may underlie expectations of varying complexity, which could be related to different sources of object vs. feature expectations in the brain.